The field of the invention is systems and methods for magnetic resonance imaging (“MRI”). More particularly, the invention relates to systems and methods for accelerated three-dimensional image data acquisition with an MRI system.
MRI uses the nuclear magnetic resonance (“NMR”) phenomenon to produce images. When a substance such as human tissue is subjected to a uniform magnetic field (“main magnetic field”), B0, the individual magnetic moments of the nuclei in the tissue attempt to align with this magnetic field, but precess about it in random order at their characteristic Larmor frequency, ω. If the substance, or tissue, is subjected to an excitation magnetic field, B1, that is in the plane transverse to the main magnetic field, B0, and that is near the Larmor frequency, ω, the net aligned magnetic moment of the nuclei may be rotated, or “tipped,” into the transverse plane to produce a net transverse magnetic moment. A signal is emitted by the excited nuclei, or “spins,” after the excitation magnetic field, B1, is terminated. The emitted signal may be received and processed to form an image.
When utilizing these emitted “MR” signals to produce images, magnetic field gradients (Gx, Gy, and Gz) are employed. Typically, the region to be imaged is scanned by a sequence of measurement cycles in which these gradients vary according to the particular localization method being used. The resulting set of received MR signals are digitized and processed to reconstruct the image using one of many well known reconstruction techniques.
The measurement cycle used to acquire each MR signal is performed under the direction of a pulse sequence produced by a pulse sequencer. Clinically available MRI systems store a library of such pulse sequences that can be prescribed to meet the needs of many different clinical applications. Research MRI systems include a library of clinically-proven pulse sequences and they also enable the development of new pulse sequences.
Depending on the technique used, many MR scans currently require many minutes to acquire the necessary data used to produce medical images. The reduction of this scan time is an important consideration, since reduced scan time increases patient throughout, improves patient comfort, and improves image quality by reducing motion artifacts. Many different strategies have been developed to shorten the scan time.
One such strategy is referred to generally as “parallel MRI” (“pMRI”). Parallel MRI techniques use spatial information from arrays of radio frequency (“RF”) receiver coils to substitute for the spatial encoding that would otherwise have to be obtained in a sequential fashion using RF pulses and magnetic field gradients, such as phase and frequency encoding gradients. Each of the spatially independent receiver coils of the array carries certain spatial information and has a different spatial sensitivity profile. This information is utilized in order to achieve a complete spatial encoding of the received MR signals, for example, by combining the simultaneously acquired data received from each of the separate coils. Parallel MRI techniques allow an undersampling of k-space by reducing the number of acquired phase-encoded k-space sampling lines, while keeping the maximal extent covered in k-space fixed. The combination of the separate MR signals produced by the separate receiver coils enables a reduction of the acquisition time required for an image, in comparison to a conventional k-space data acquisition, by a factor related to the number of the receiver coils. Thus the use of multiple receiver coils acts to multiply imaging speed, without increasing gradient switching rates or RF power.
Two categories of such parallel imaging techniques that have been developed and applied to in vivo imaging are so-called “image space methods” and “k-space methods.” An example of an image space method is known in the art as sensitivity encoding (“SENSE”), while an example of a k-space method is known in the art as simultaneous acquisition of spatial harmonics (“SMASH”). With SENSE, the undersampled k-space data is first Fourier transformed to produce an aliased image from each coil, and then the aliased image signals are unfolded by a linear transformation of the superimposed pixel values. With SMASH, the omitted k-space lines are synthesized or reconstructed prior to Fourier transformation, by constructing a weighted combination of neighboring k-space lines acquired by the different receiver coils. SMASH requires that the spatial sensitivity of the coils be determined, and one way to do so is by “autocalibration” that entails the use of variable density k-space sampling.
A more recent advance to SMASH techniques using autocalibration is a technique known as generalized autocalibrating partially parallel acquisitions (“GRAPPA”), as described, for example, in U.S. Pat. No. 6,841,998. With GRAPPA, k-space lines near the center of k-space are sampled at the Nyquist frequency, in comparison to the undersampling employed in the peripheral regions of k-space. These center k-space lines are referred to as the so-called autocalibration signal (“ACS”) lines, which are used to determine the weighting factors that are utilized to synthesize, or reconstruct, the missing k-space lines. In particular, a linear combination of individual coil data is used to create the missing lines of k-space. The coefficients for the combination are determined by fitting the acquired data to the more highly sampled data near the center of k-space.
Conventional parallel MRI techniques rely on accelerating standard image acquisitions by undersampling k-space. For example, these methods undersample k-space by reducing the number of phase-encodings acquired during each repetition of a pulse sequence. In three-dimensional acquisitions, k-space can be further undersampled along the partition-encoding direction, which may also be referred to as a second phase-encoding direction.
Recent modifications to standard rectilinear 3D k-space sampling trajectories have provided more robust parallel imaging reconstructions of highly undersampled datasets. For example, in the 2D CAIPIRINHA method described by F. A. Breuer, et al., in “Controlled Aliasing in Volumetric Parallel Imaging (2D CAIPIRINHA),” Magnetic Resonance in Medicine, 2006; 55(3):549-556, the phase encoding sampling strategy is modified to shift the spatial aliasing pattern to reduce aliasing and to better exploit coil sensitivity variations. In another method referred to as bunched phase encoding (“BPE”) and described by H. Moriguchi and J. L. Duerk in “Bunched Phase Encoding (BPE): A New Fast Data Acquisition Method in MRI,” Magnetic Resonance in Medicine, 2006; 55(3):633-648, an alternating phase-encoding gradient is applied during the readout of each k-space line to create a zigzag trajectory so that multiple k-space lines can be simultaneously acquired. The image data acquired using the BPE method can be reconstructed using Papoulis's generalized sampling theory to give an alias-free image. BPE has also been combined with parallel imaging, whereby the zigzag trajectory allows for utilization of the coil sensitivity variation in the readout direction to improve reconstruction. While both of these methods provide for improvements in three-dimensional acquisitions, they still suffer from g-factor related SNR reductions common to parallel imaging acquisitions and reconstructions.
In general, the 2D CAIPIRINHA and BPE methods seek to reduce the g-factor penalty of parallel imaging by improving the sampling pattern of the accelerated k-space trajectory, thereby spreading the aliasing patterns in a manner more favorable to separating the aliased signals. However, at high acceleration factors, the benefits that these methods provide to this end are limited.
It would therefore be desirable to provide a method for accelerated three-dimensional MRI, in which increased acceleration can be utilized without detrimentally affecting the g-factor performance of the data acquisition.